With the rapid development of computer and Internet technologies, many services can be performed on the Internet. Graph computing is a common means for processing social online services.
For example, for identification of fraud on accounts in a social risk control service, each user is considered as a node. If there is a transfer relationship between two users, a line is present between two corresponding nodes. The line may be directionless, or may be directed according to a transfer direction. In this way, graph data including a plurality of nodes and lines may be obtained, to perform graph computing based on the graph data to implement risk control.
A random walk algorithm is a relatively basic and important part of graph computing, and provides support for an upper-level complex algorithm. In existing technologies, the following random walk algorithm is generally used: Any node included in graph data is read in a database, any adjacent node of the node is further read in the database, to implement random walking in the graph data.
Based on the existing technologies, a more efficient random walking solution applicable to large-scale graph data is needed.